binary linear classifiers

(45 minutes to learn)


A linear classifier makes a classification decision for a given observation based on the value of a linear combination of the observation's features. In a ``binary'' linear classifier, the observation is classified into one of two possible classes using a linear boundary in the input feature space.


This concept has the prerequisites:

Core resources (read/watch one of the following)


Optimization Models and Applications

Supplemental resources (the following are optional, but you may find them useful)


See also